Table of Contents Author Guidelines Submit a Manuscript
Abstract and Applied Analysis
Volume 2014, Article ID 728564, 11 pages
http://dx.doi.org/10.1155/2014/728564
Research Article

Wavelets Application in Prediction of Friction Stir Welding Parameters of Alloy Joints from Vibroacoustic ANN-Based Model

1Electrical Engineering Department, University of La Rioja, 26004 Logroño, Spain
2Faculty of Mechanical Engineering, University of Oriente, 90900 Santiago de Cuba, Cuba
3Mechanical Engineering Department, University of La Rioja, 26004 Logroño, Spain

Received 1 March 2014; Accepted 23 March 2014; Published 18 May 2014

Academic Editor: Eugene B. Postnikov

Copyright © 2014 Emilio Jiménez-Macías et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. G. M. Xie, Z. Y. Ma, and L. Geng, “Development of a fine-grained microstructure and the properties of a nugget zone in friction stir welded pure copper,” Scripta Materialia, vol. 57, no. 2, pp. 73–76, 2007. View at Publisher · View at Google Scholar
  2. G. Buffa, L. Fratini, and F. Micari, “A neural network based approach for the design of FSW processes,” Key Engineering Materials, vol. 410-411, pp. 413–420, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. H. Okuyucu, A. Kurt, and E. Arcaklioglu, “Artificial neural network application to the friction stir welding of aluminum plates,” Materials and Design, vol. 28, no. 1, pp. 78–84, 2007. View at Publisher · View at Google Scholar · View at Scopus
  4. T. Jene, G. Dobmann, G. Wagner, and D. Eifler, “Monitoring of the friction stir welding process to describe parameter effects on joint quality,” Welding in the World, vol. 52, no. 9-10, pp. 47–53, 2008. View at Google Scholar · View at Scopus
  5. E. Castillo, D. P. Morales, A. García, F. Martínez-Martí, L. Parrilla, and A. J. Palma, “Noise suppression in ECG signals through efficient one-step wavelet processing techniques,” Journal of Applied Mathematics, vol. 2013, Article ID 763903, 13 pages, 2013. View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  6. R. Li and Y. M. Liu, “Wavelet optimal estimations for density functions under severely ill-posed noises,” Abstract and Applied Analysis, vol. 2013, Article ID 260573, 7 pages, 2013. View at Publisher · View at Google Scholar
  7. V. Soundararajan, H. Atharifar, and R. Kovacevic, “Monitorinf and processing the acoustic emission signals from the friction-stir-welding process,” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, vol. 220, no. 10, pp. 1673–1685, 2006. View at Publisher · View at Google Scholar · View at Scopus
  8. C. N. Suresha, B. M. Rajaprakash, and U. Sarala:, “Applicability of acoustic emission in the analysis of friction stir welded joints,” International Journal of Recent Trends in Engineering, vol. 1, no. 5, pp. 86–89, 2009. View at Google Scholar
  9. A. S. Roca, H. C. Fals, E. J. Macías, J. B. Fernández, and F. S. Adán, “Time-frequency diagram applied to stability analysis in gas metal arc welding based on acoustic emission,” Science and Technology of Welding and Joining, vol. 15, no. 3, pp. 226–232, 2010. View at Publisher · View at Google Scholar
  10. E. J. Macías, A. S. Roca, H. C. Fals, J. B. Fernández, and M. P. de la Parte, “New stability index for short circuit transfer mode in GMAW process using acoustic emission signals,” Science and Technology of Welding and Joining, vol. 12, no. 5, pp. 460–466, 2007. View at Publisher · View at Google Scholar
  11. J. B. Fernández, A. S. Roca, H. C. Fals, E. J. Macias, and M. P. de la Parte, “Application of vibroacoustic signals to evaluate tools profile changes in friction stir welding on AA 1050 H24 alloy,” Science and Technology of Welding and Joining, vol. 17, pp. 501–510, 2012. View at Google Scholar
  12. J. X. Shen and W. Li, “Sensitivity analysis of wavelet neural network model for short-term traffic volume prediction,” Journal of Applied Mathematics, vol. 2013, Article ID 953548, 10 pages, 2013. View at Publisher · View at Google Scholar
  13. Y. D. Song, Q. Cao, X. Du, and H. R. Karimi, “Control strategy based on wavelet transform and neural network for hybrid power system,” Journal of Applied Mathematics, vol. 2013, Article ID 375840, 8 pages, 2013. View at Publisher · View at Google Scholar
  14. K. Dimililer, “Backpropagation neural network implementation for medical image compression,” Journal of Applied Mathematics, vol. 2013, Article ID 453098, 8 pages, 2013. View at Publisher · View at Google Scholar
  15. G. G. Wang, L. H. Guo, and H. Duan, “Wavelet neural network using multiple wavelet functions in target threat assessment,” The Scientific World Journal, vol. 2013, Article ID 632437, 7 pages, 2013. View at Publisher · View at Google Scholar
  16. Y. K. Yousif, K. M. Daws, and B. I. Kazem, “Prediction of friction stir Welding characteristic using neural network,” Jordan Journal of Mechanical and Industrial Engineering, vol. 2, no. 3, pp. 151–155, 2008. View at Google Scholar
  17. E. J. Macías, A. S. Roca, H. C. Fals, J. B. Fernández, and J. C. S. Muro, “Neural networks and acoustic emission for modelling and characterization of the friction stir welding process,” Revista Iberoamericana de Automática e Informática Industrial RIAI, vol. 10, no. 4, pp. 434–440, 2013. View at Publisher · View at Google Scholar
  18. I. N. Tansel, M. Demetgul, H. Okuyucu, and A. Yapici, “Optimizations of friction stir welding of aluminum alloy by using genetically optimized neural network,” International Journal of Advanced Manufacturing Technology, vol. 48, no. 1–4, pp. 95–101, 2010. View at Publisher · View at Google Scholar · View at Scopus
  19. K. Lakshminarayanan and V. Balasubramanian, “Comparison of RSM with ANN in predicting tensile strength of friction stir welded AA7039 aluminium alloy joints,” Transactions of Nonferrous Metals Society of China, vol. 19, no. 1, pp. 9–18, 2009. View at Publisher · View at Google Scholar
  20. X. J. Yang, D. Baleanu, H. M. Srivastava, and J. A. T. Machado, “On local fractional continuous wavelet transform,” Abstract and Applied Analysis, vol. 2013, Article ID 725416, 5 pages, 2013. View at Publisher · View at Google Scholar
  21. W. Q. Song, Q. Li, Qing Li, and Y. M. Wang, “Tool wear detection using lipschitz exponent and harmonic wavelet,” Mathematical Problems in Engineering, vol. 2013, Article ID 489261, 8 pages, 2013. View at Publisher · View at Google Scholar
  22. C. Chen, R. Kovacevic, and D. Jandgric, “Wavelet transform analysis of acoustic emission in monitoring friction stir welding of 6061 aluminum,” International Journal of Machine Tools and Manufacture, vol. 43, no. 13, pp. 1383–1390, 2003. View at Publisher · View at Google Scholar · View at Scopus
  23. M. S. Orozco, E. J. Macías, A. S. Roca, H. C. Fals, and J. B. Fernández, “Optimisation of friction-stir welding process using vibro-acoustic signal analysis,” Science and Technology of Welding and Joining, vol. 18, no. 6, pp. 532–540, 2013. View at Google Scholar